The impact of air pollution on people and the environment is a severe issue that has recently been the subject of extensive research. This study has looked at the factors that contribute to the seasonal and spatial variability of pollutant concentration over Delhi NCR from 2019 to 2021. Additionally, the causes of changes in air quality during the COVID-19’s lockdown period in 2020 have been discussed, along with comparisons to the pre-lockdown year (2019) and the post-lockdown year (2021). Seven pollutant parameters, viz., (PM2.5, PM10, NOx, CO, SO2, NH3, and O3) were retrieved from the air quality monitoring stations spread over Delhi NCR. The results show a significant temporal (seasonal) and spatial variability in the air pollutants’ concentration. The highest pollutant level was observed in winter and the lowest in summer seasons. The results suggest that the concentration of atmospheric pollutants was already lower (20–30%) before the implementation of the lockdown. Meteorology played an important role in emission reduction during the lockdown, in particular, and seasonal, in general. The results also suggest that Bhiwadi is not the most polluted city, as claimed in the World Air Quality Report 2022. The most polluted sites in terms of pollutant concentration were observed over Delhi in all the years considered. @en

Every year at the onset of winter season (October–November), crop residue/parali/stubble burning starts in Punjab and Haryana, leading to heavy air pollution in Delhi, and adversely affecting human and environmental health. During this time, the combination of unfavourable meteorological conditions, additional emissions from stubble burning, and firework activities in this area causes the air quality to further deteriorate. In this study, we have attempted to understand the influence of parali and firecracker incidents on air pollutants’ variability over Delhi during the last three years (2020 to 2022). For this purpose, daily average particulate matter and gaseous pollutants data were fetched from the Central Pollution Control Board (CPCB), and daily total fire counts and fire radiative power (FRP) data were retrieved from NASA’s Fire Information for Resource Management System (FIRMS). A bigger area of severe burning is suggested by higher FRP values and higher fire counts in the middle of November in all the years considered. Three years satellite-based FIRMS data over Punjab and Haryana show the highest number of active fire counts in 2021 (n = 80,505) followed by 2020 (n = 75,428), and 2022 (n = 49,194). More than 90% parali burning incidents were observed in Punjab state only despite the considerable variability in numbers among the years. The significant effect of parali burning was seen on pollutant concentration variability. As the number of fire count increases or decreases in Punjab and Haryana, there is a corresponding increase or decrease in the particulate matter concentration with a time lag of few days (1 to 2 days). The trend in backward air mass trajectories suggests that the variable response time of pollutants’ concentration is due to local and distant sources with different air mass speeds. Our estimates suggest that stubble burning contributes 50–75% increment in PM_2.5 and 40 to 45% increase in PM₁₀ concentration between October and November. A good positive correlation between PM_2.5, PM₁₀, NO_X, and CO and fire counts (up to 0.8) suggests a strong influence of stubble burning on air quality over Delhi. Furthermore, the firecracker activities significantly increase the concentration of particulate matter with ~100% increment in PM_2.5 and ~55% increment in PM₁₀ mass concentrations for a relatively shorter period (1 to 2 days).

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In this study, the relationships between meteorological parameters (relative humidity, wind speed, temperature, planetary boundary layer, and rainfall) and air pollutants (particulate matter and gaseous pollutants) have been evaluated during a 3-year period from 2019 to 2021. Diffusion and dispersion of air contaminants were significantly influenced by meteorology over the capital city. The results of correlation matrix and principal component analysis (PCA) suggest a season’s specific influence of meteorological parameters on atmospheric pollutants’ concentration. Temperature has the strongest negative impact on pollutants’ concentration, and all the other studied meteorological parameters negatively (reduced) as well as positively (increased) impacted the air pollutants’ concentration. A two-way process was involved during the interaction of pollutants with relative humidity and wind speed. Due to enhanced moisture-holding capacity during non-monsoon summers, particles get larger and settle down on the ground via dry deposition processes. Winter’s decreased moisture-holding capacity causes water vapour coupled with air contaminants to remain suspended and further deteriorate the quality of the air. High wind speed helps in the dispersion and dilution but a high wind speed associated with dust particles may increase the pollutants’ level downwind side. The PM_2.5/PM₁₀ variation revealed that the accumulation effect of relative humidity on PM_2.5 was more intense than PM₁₀. Daily average location-specific rainfall data revealed that moderate to high rainfall has a potential wet scavenging impact on both particulate matters and gaseous pollutants.

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